• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1250-1258
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• 2017

The multigroup transport theory is the basis for many neutronics modules. A significant point of the cross-section (XS) generation procedure is the choice of the energy groups' boundaries in the XS libraries, which must be carefully selected as an unsuitable energy meshing can easily lead to inaccurate results. This decision can require considerable effort and is particularly difficult for the common user, especially if not well-versed in reactor physics. This work investigates a genetic algorithm-based tool which selects an appropriate XS energy structure (ES) specific for the considered problem, to be used for the condensation of a fine multigroup library. The procedure is accelerated by results storage and fitness calculation speedup and can be easily parallelized. The extension is applied to the coupled code SIMMER and tested on the European Sustainable Nuclear Industrial Initiative (ESNII+) Advanced Sodium Technological Reactor for Industrial Demonstration (ASTRID)-like reactor system with different fitness functions. The results show that, when the libraries are condensed based on the ESs suggested by the algorithm, the code actually returns the correct multiplication factor, in both reference and voided conditions. The computational effort reduction obtained by using the condensed library rather than the fine one is assessed and is much higher than the time required for the ES search.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.328-334
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• 2021

The article examines the economic essence and approaches to determining the efficiency of the enterprise. The author in the study considers the effectiveness and from the standpoint of qualitative analysis of the effectiveness of change and implementation of enterprise development goals. It is established that the tool for ensuring qualitative impacts on the efficiency of the enterprise is the innovative development of the economic space of the enterprise. The article considers the dominant innovations that have influenced the means and methods of production. An organizational and economic mechanism has been recommended to coordinate the costs of innovation activities in order to ensure the efficiency of enterprises. The object of management in the organizational and economic mechanism is the innovation process in the enterprise: from the design of strategic goals of innovation, search and commercialization of innovations, to building and implementing innovation potential. The efficiency of the enterprise under the condition of realization of innovative potential will be characterized by steady competitive advantages and strategically-oriented behavior in the market.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.29 no.2
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• pp.67-69
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• 2018

The development of office-based, unsedated transnasal esophagoscopy (TNE) has proven to be a major technological advance and with time and experience the application of this technology is becoming more widespread. TNE has allowed otolaryngologists to perform a variety of diagnostic and therapeutic procedures in the office setting. Studies consistently demonstrate that the image quality and diagnostic capability of TNE is equivalent to conventional esophagoscopy. The modern TNE endoscopes offer high quality optics, air-insufflation, and irrigation capability through a 2-mm working channel, and the ability to perform biopsies and select procedures. In general, the role of TNE in the head and neck patient is three-fold : to screen for synchronous and metachronous esophageal squamous cell carcinoma (ESCC) ; to differentiate post-treatment changes/symptoms from malignancy ; and to perform certain office-based procedures. TNE offers many specific advantages to the head and neck patient that are not afforded by conventional esophagoscopy. Because of surgical and postirradiation changes, many HNSCC patients have trismus or neck stiffness preventing completion of conventional transoral esophagoscopy. Perhaps most importantly, TNE provides enhanced patient safety, increased tolerability, better practice efficiency, and cost savings. For these reasons, TNE has become a particularly useful tool in the otolaryngologist's armamentarium.

• 한국벤처창업학회:학술대회논문집
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• 2018.11a
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• pp.269-275
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• 2018

Electronic commerce, the act of trading online, with its myriad of potential has been seldom looked at within the context of developing countries. E-commerce presents SMEs in developing economies the opportunity to adequately compete on a global stage. The exponential growth of e-commerce in developed economies further widens the financial gap between developed and developing economies. This study looks at a practical e-commerce adoption framework for Ghanaian SMEs and by extension, developing economies and looks at the net benefits that are available to current adopters. The study uses structural equation modeling, using Partial least squares (PLS) regression to analyze the data in the research. Using PLS algorithms as well as bootstrapping calculations. It combines the use of surveys (154) and interviews (38) as means of data collection. The findings of the research indicate that there is a need for legislation on e-commerce trading to regulate the trade in Ghana, with policies such as e-contracting and e-signature laws among others. Also, a current call for an expansion of the mobile payment methods within the country. For the private investor, a ripe market for logistics services. The study also proposes a simple guideline for SMEs looking to adopt or expand their e-commerce usage, that considers technological, organizational and environmental factors that come to play within e-commerce adoption.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.187-195
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• 2021

The intensification of the processes of the digital economy development is leading to the transformation of the higher education system. Universities are forced to digitalize their own educational, research, international, marketing, financial and economic activities in order to maintain a competitive position in the global market of educational services. The purpose of the article is to study the role of information and communication technologies in the development of the higher education system and to ensure its adaptability to modern challenges of digital economy. To achieve this goal, methods of content analysis, logical generalization, systematization and a structural-functional method are used. In the article, the authors substantiate the urgency of forming a holistic strategy to ensure the adaptability of higher education to the challenges of digital economy. In the structure of this strategy, the information-technological block is singled out and described. The authors specified a set of positive synergetic effects from the introduction of modern information and communication technologies in the activities of universities. The main information threats to the digitalization of higher education related to the protection of personal data and university systems from cyberattacks and fraudulent schemes are identified. In conclusion, the authors detail the measures for the strategy implementation to ensure the adaptability of higher education to digital economy.

• ETRI Journal
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• v.44 no.4
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• pp.613-623
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• 2022

Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment, the provision of family support, and for providing appropriate medical support for the child on time. Thus, developing automated methods for diagnosing ASD is becoming an essential need. Herein, we investigate using various machine learning methods to build predictive models for diagnosing ASD in children using facial images. To achieve this, we used an autistic children dataset containing 2936 facial images of children with autism and typical children. In application, we used classical machine learning methods, such as support vector machine and random forest. In addition to using deep-learning methods, we used a state-of-the-art method, that is, automated machine learning (AutoML). We compared the results obtained from the existing techniques. Consequently, we obtained that AutoML achieved the highest performance of approximately 96% accuracy via the Hyperpot and tree-based pipeline optimization tool optimization. Furthermore, AutoML methods enabled us to easily find the best parameter settings without any human efforts for feature engineering.

• Current Photovoltaic Research
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• v.11 no.4
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• pp.124-133
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• 2023

In order to deploy the large-scale energy storage (ES) service in the various industry, it is very important to develop a business model with high technological and economic feasibility through detailed valuation of cost and expected benefits. In relation to this, this paper established an optimal scheduling plan for electric vehicle charging stations connected with photovoltaic (PV) and ES technologies in Korea using the distributed energy resource valuation tool and analyzed the feasibility of the project. In addition, the impact of incentives such as REC (Renewable Energy Certificate) to be given to electric vehicle charging stations in accordance with the relevant laws to be revised in the future was analyzed. As a results, the methodology presented in this paper are expected to be used in various ways to analyze the feasibility of various business models linked to renewable energy and ES technologies as well as the electric vehicle market.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.1118-1134
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• 2023

Previous research has shown that employees tend to react more positively to corrective feedback from supervisors to the extent they perceive that they were treated with empathy, respect, and concern towards fair interpersonal treatment in receiving the feedback information. Then, to facilitate effective supervisory feedback and coaching, it would be useful for organizations to monitor the contents of feedback exchanges between supervisors and employees to make sure that supervisors are providing performance feedback using languages that are more likely to be perceived as interpersonally fair. Computer-aided text analysis holds potential as a useful tool that organizations can use to efficiently monitor the quality of the feedback messages that supervisors provide to their employees. In the current study, we applied computer-aided text analysis (using closed-vocabulary text analysis) and machine learning to examine the validity of language-based algorithms trained on supervisor language in performance feedback situations for predicting human ratings of feedback interpersonal fairness. Results showed that language-based algorithms predicted feedback interpersonal fairness with reasonable level of accuracy. Our findings provide supportive evidence for the promise of using employee language data for managing (and improving) performance management in organizations.

• Journal of Distribution Science
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• v.22 no.1
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• pp.1-12
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• 2024

Purpose: Rapid technological advancements and information dissemination have catalyzed a steep upsurge in the distribution of ornamental flower arrangement products, effectively meeting the burgeoning demands of customers. This research endeavours to elucidate the relationship between market orientation (MO) and competitive advantage (CA), with the intermediary role of marketing performance (MP) within Denpasar's flower arrangement retail sector. Research Methods: Conducted within a Denpasar-based flower shop, the study engaged 94 respondents through a questionnaire-based data collection methodology. Utilizing a saturated sampling approach, the sample size equated to the population size. The analysis employed SmartPLS, a robust statistical tool. Results: The study findings reveal that MO does not exert a statistically significant direct impact on CA. Nevertheless, MO exhibits a substantively positive and statistically significant influence on MP, which, in turn, substantially and significantly contributes to CA. For flower arrangement business owners, it is imperative to orchestrate effective control over their marketing performance. Conclusion: This involves nurturing enduring customer and employee relationships by steadily implementing market-oriented distribution strategies. By doing so, customer satisfaction and growth, pivotal in bolstering marketing performance, can be adeptly sustained, ultimately culminating in attaining competitive advantage.

• Korean Journal of Radiology
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• v.25 no.6
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• pp.518-539
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• 2024

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations.